Group inference based upon venue zone events

ABSTRACT

Zone events are tracked within a venue. The zone events represent relative movements and dwelling times of multiple mobile devices within the venue as users of the respective mobile devices move and dwell among and within multiple configured zones of the venue. A relationship is inferred between at least two of the users responsive to a configured zone event threshold being satisfied by the tracked zone events that represent the relative movements and dwelling times of the mobile devices of the at least two users.

BACKGROUND

The present invention relates to automated determination ofinterpersonal groups according to wireless device dwell and movementevents within a venue. More particularly, the present invention relatesto group inference based upon venue zone events.

Users of mobile devices may carry the mobile devices with them as theytravel during a course of any given day. The users may use the mobiledevices to make telephone calls, to send and receive electronic mailmessages (email), and to connect to Internet-based websites from anylocation that has suitable wireless network connectivity or WirelessFidelity (Wi-Fi) connectivity for the communication platform(s)supported by the respective mobile devices.

SUMMARY

A computer-implemented method includes tracking, within a venue by aprocessor, zone events that represent relative movements and dwellingtimes of multiple mobile devices within the venue as users of therespective mobile devices move and dwell among and within multipleconfigured zones of the venue; and inferring a relationship between atleast two of the users responsive to a configured zone event thresholdbeing satisfied by the tracked zone events that represent the relativemovements and dwelling times of the mobile devices of the at least twousers.

A system that performs the computer-implemented method and a computerprogram product that causes a computer to perform thecomputer-implemented method are also described.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a cloud computing node according to an embodiment of thepresent invention;

FIG. 2 depicts a cloud computing environment according to an embodimentof the present invention;

FIG. 3 depicts abstraction model layers according to an embodiment ofthe present invention;

FIG. 4 is a flow chart of an example of an implementation of a processfor group inference based upon venue zone events according to anembodiment of the present subject matter; and

FIG. 5 is a flow chart of an example of an implementation of a processfor group inference based upon venue zone events that further infersgroups of users according to multiple different and granular venue zoneevents according to an embodiment of the present subject matter.

DETAILED DESCRIPTION

The examples set forth below represent the necessary information toenable those skilled in the art to practice the invention and illustratethe best mode of practicing the invention. Upon reading the followingdescription in light of the accompanying drawing figures, those skilledin the art will understand the concepts of the invention and willrecognize applications of these concepts not particularly addressedherein. It should be understood that these concepts and applicationsfall within the scope of the disclosure and the accompanying claims.

The subject matter described herein provides group inference based uponvenue zone events. The present technology solves a recognized venuelocation-based group identification problem by providing technology thatincludes a new form of detection of relationships between users ofmobile devices. The technology tracks several venue zone-based eventsassociated with mobile devices carried by users within one or morevenues. For example, the technology tracks mobile devices as therespective users enter into venue zones, tracks mobile devices as therespective users move within venue zones, tracks mobile devices as therespective users stay/dwell at different locations within venue zones,and tracks mobile devices as the respective users move between/amongvenue zones within a particular venue. From this information, thetechnology may then infer user relationships, such as interpersonalgroups (e.g., friends, family, etc.). As such, the present technologymay infer groups of users from their respective and related movements(e.g., similar browsing patterns) within one or more venues inaccordance with locations and movements of their respective mobiledevices as the users move and dwell together within the venue(s).

For purpose of the present description, a “venue” may include anylocation that may be configured with zones using short-distance wirelessdevice location detection technology (e.g., Bluetooth low energy (BLE)or other hotspot beacons, triangulation, proximity, etc.), such as asports coliseum, a store, a shopping mall, a food court within ashopping mall, or other type of area where people gather and move amongdifferent locations within the area. A venue “zone” may include an areaor region of a venue, such as a food court/cafeteria or soda shop withina shopping mall or sports stadium, a section of a department store(e.g., clothing, shoes, etc.), an arcade, or other area/region that maybe configured with short-distance wireless device location detectiontechnology to detect movement among and within the respectivearea/region, and users dwelling within that area/region.

A venue “zone event” refers to detection of a mobile device (and therebythe respective user carrying the mobile device) entering, moving within,dwelling at a location within, and leaving a particular venue zone.Multiple different forms of zone events may be configured as granularlyas appropriate for the particular zone according to size and otherfactors related to the particular zone (e.g., number and proximity ofshelving or display units, etc.). The terms “dwell” and “dwell time”refer to a user of a mobile device being detected as remaining in aparticular location/zone for a particular duration of time. The term“dwell pattern” refers to coincident dwell times within venue zones ofdifferent mobile device users. The term “browsing patterns” referscollectively to coincident movements within and among venue zones incombination with dwell patterns of different mobile device users as theyjourney through a venue. Additionally, the term “related” for purposesof inference of groups based upon venue zone events refers to usersbeing friends, acquaintances, family members, or having any otherrelationship where the users know one another and/or develop arelationship during a course of coincident browsing patterns within avenue (e.g., talking about an item and realizing common interests thatresult in an interpersonal relationship, etc.).

The technology described herein operates by tracking, within a venue,zone events that represent relative movements and dwelling times ofmultiple mobile devices within the venue as users of the respectivemobile devices move and dwell among and within multiple configured zonesof the venue. The technology further operates by inferring arelationship between at least two of the users responsive to aconfigured zone event threshold being satisfied by the tracked zoneevents that represent the relative movements and dwelling times of themobile devices of the at least two users.

The present technology analyzes movements and dwelling patterns ofmobile device user's as they enter, exit, and remain within one or morevenues and/or zones to determine how long different users stand (e.g.,dwell/remain/stay) in certain areas of the venues and the respectiveusers' movement patterns within the venues relative to other users. Thisdwell and movement information of different users may be used todetermine a likelihood or probability of different users being related.It should be noted that the users may be provided with an opportunity to“opt in” to the location tracking technology described herein.

A number of preferences regarding when to “infer” a relationship betweenor among a group of different users may be established and configured.For example, a threshold zone entry time may be established, such thatdifferent users entering a zone within a configured time of each othermay be inferred to be related (e.g., users entering a zone within one(1) minute of each other, within five (5) minutes of each other, etc.).If the users enter a zone within the configured threshold zone entrytime, the users may be inferred to be related.

Further, a threshold zone exit time may be established, such thatdifferent users exiting a zone within a configured time of each othermay be inferred to be related (e.g., users exiting a zone within one (1)minute of each other, within five (5) minutes of each other, etc.). Ifthe users exit a zone within the configured threshold zone exit time,the users may be inferred to be related.

Additionally, a threshold distance of movement over time may beestablished, such that different users remaining within a configureddistance of each other as they move among/between and/or within zonesmay be used to infer a relationship between the users (e.g., usersremaining within ten (10) feet of each other, within five (5) feet ofeach other, etc.). If the users remain within the configured thresholddistance while moving, the users may be inferred to be related.

Additionally, a threshold number of similar movements may beestablished, such as a number of times that different users movetogether among or within zones (e.g., one (1) time, two (2) times, three(3) times, etc.). If the users move together more than the configuredthreshold number of similar movements, the users may be inferred to berelated.

Further, a threshold shared dwell time may be established, such as anamount of time different users remain near one another within a zone(e.g., dwell for over five (5) minutes, ten (10) minutes, etc.). If theusers dwell together more than the configured threshold shared dwelltime, the users may be inferred to be related.

As another alternative, a threshold number of common zones at commontimes may be established, such as a number of time different users enterthe same zones during the course of their respective time at a venueduring the same time intervals (e.g., ten (10) or more total zonesvisited by each of different users, with (6) zone visits occurring atthe same time, etc.). As such, if two users are shopping together andalso have their own browsing habits, but tend to meet each otherthroughout the shopping trip routinely more than the configuredthreshold number of common zones at common times, the users may beinferred to be related.

It should be understood that many other possibilities exist forconfiguring threshold preferences as appropriate for a given venue. Anysuch possibilities are considered to be within the scope of the presentsubject matter.

Once any of the configured thresholds is met, the relationship betweenthe users may be documented and stored. The documented relationship maybe used to provide promotions or other benefits to the respective users.The relationship may be further shared with marketing teams foradditional promotions/offers based upon the inferred relationship.

For example, a push notification may be sent to one or more of therelated users, such as to notify one of the related users that anotherof the related users is interested in an item. A coupon/discount may beprovided to the notified user, and this user may then either obtain theitem for the other related user or may assist the related user with thebenefit of the coupon/discount in purchasing the item of interest to theother user. Again, many possibilities exist for use of the inferredgroups based upon venue zone events described herein, and all suchpossibilities are considered within the scope of the presentdescription.

As such, the present technology may identify related users (groups)according to venue zone events that may not otherwise be detectable. Thetechnology may additionally provide notifications and improve benefitsderived from the users' group relations.

It should be noted that conception of the present subject matterresulted from recognition of certain limitations associated withidentification of relationships between people. For example, it wasobserved that it would be beneficial to users, such as shoppers, sportsfans, and other people, to have their relationships inferred and to beprovided with benefits (reminders such as birthdays, anniversaries,etc.; promotions; and other benefits) that are of relevance to theirrelationships with other people. It was further determined that absolutelocation technologies, such as global positioning system (GPS), was notcapable of discerning zones within venues because these technologiesrely upon absolute location and do not include a sensor that may beplaced within a venue to detect movement of mobile devices near thesensor. Further, it was determined that short-distance wireless devicelocation detection technology, as described above, may be positionedwithin and/or at boundaries of locations in a venue to define zoneswithin the venue, and to detect mobile device movement and dwelling nearor within the defined zones. The present subject matter improvesinference of groups by providing for automated group inference basedupon venue zone events, as described above and in more detail below. Assuch, improved inference of groups may be obtained through use of thepresent technology.

The group inference based upon venue zone events described herein may beperformed in real time to allow prompt identification of groups ofmobile device users. For purposes of the present description, real timeshall include any time frame of sufficiently short duration as toprovide reasonable response time for information processing acceptableto a user of the subject matter described. Additionally, the term “realtime” shall include what is commonly termed “near real time”—generallymeaning any time frame of sufficiently short duration as to providereasonable response time for on-demand information processing acceptableto a user of the subject matter described (e.g., within a portion of asecond or within a few seconds). These terms, while difficult toprecisely define are well understood by those skilled in the art.

Additionally, the present technology may be implemented within or aspart of a cloud computing environment (e.g., for data analytics), or maybe implemented as a customized retail-environment specific solution. Assuch, examples of implementations for both environments are includedherein.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10 there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via Input/Output(I/O) interfaces 22. Still yet, computer system/server 12 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20. As depicted, network adapter 20communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and group inference based upon venue zoneevents 96.

FIG. 4 through FIG. 5 described below represent example processes thatmay be executed by devices, such as the cloud computing node 10, toperform the automated group inference based upon venue zone eventsassociated with the present subject matter. Many other variations on theexample processes are possible and all are considered within the scopeof the present subject matter. It should be noted that time outprocedures and other error control procedures are not illustrated withinthe example processes described below for ease of illustration purposes.However, it is understood that all such procedures are considered to bewithin the scope of the present subject matter. Further, the describedprocesses may be combined, sequences of the processing described may bechanged, and additional processing may be added or removed withoutdeparture from the scope of the present subject matter.

FIG. 4 is a flow chart of an example of an implementation of a process100 for group inference based upon venue zone events. The process 100represents a computer-implemented method of performing the subjectmatter described herein. At block 102, the process 100 tracks, within avenue by a processor, zone events that represent relative movements anddwelling times of multiple mobile devices within the venue as users ofthe respective mobile devices move and dwell among and within multipleconfigured zones of the venue. At block 104, the process 100 infers arelationship between at least two of the users responsive to aconfigured zone event threshold being satisfied by the tracked zoneevents that represent the relative movements and dwelling times of themobile devices of the at least two users.

FIG. 5 is a flow chart of an example of an implementation of a process200 for group inference based upon venue zone events that further infersgroups of users according to multiple different and granular venue zoneevents. The process 200 represents a computer-implemented method ofperforming the subject matter described herein. It should be noted thatthe process 200 is depicted and described as a single flowchart for easeof illustration and description purposes. However, it shouldadditionally be noted that the process 200 is considered to bere-entrant and multi-threaded responsive to any of the representativeevents. This re-entrant and multi-threaded processing is not separatelyillustrated to reduce complexity within the drawing and description,though it is further understood that detected zone events work inconjunction with detection of additional similar zone events asappropriate for a given zone event and a given implementation of theprocess 200.

It should be noted that to avoid further crowding within the drawing,zone entry and zone exit events are combined in the drawing anddescription. However, it should further be understood that theprocessing associated with these two distinct forms of events may beperformed either independently or in a combined manner, and may furtherbe combined with other zone event processing, each as appropriate for agiven implementation.

At decision point 202, the process 200 begins higher-level iterativeprocessing to detect different zone events. Affirmative processing ateach decision point of the higher-level iterative processing will bedeferred and described in more detail further below in favor of aninitial description of the higher-level iterative processing fordetection of different zone events.

As such, at decision point 202, the process 200 makes a determination asto whether either a zone entry event or a zone exit event has beendetected responsive to a user either entering a zone or exiting a zoneof a venue. In response to determining that a zone entry event or a zoneexit event has not been detected, the process 200 makes a determinationat decision point 204 as to whether a zone movement distance event hasbeen detected responsive to multiple users beginning to move togetherwithin a configured distance. In response to determining that a zonemovement distance event has not been detected, the process 200 makes adetermination at decision point 206 as to whether a similar movementevent has been detected responsive to users making a similar movementwithin a venue (perhaps irrespective of a particular distance betweenthe users and/or the timing of zone entries). In response to determiningthat a similar movement event has not been detected, the process 200makes a determination at decision point 208 as to whether a shared dwellevent has been detected responsive to multiple users becoming stationary(e.g., standing) together within a venue. In response to determiningthat a shared dwell event has not been detected, the process 200 makes adetermination at decision point 210 as to whether a common zones atcommon times event has been detected responsive to users beingrepeatedly detected within the same zones of a venue (e.g., multiplezone overlaps, again, perhaps irrespective of a particular distancebetween the users and/or the timing of zone entries). In response todetermining that a common zone event has not been detected, the process200 returns to decision point 202 and iterates as described above.

Returning to the description of decision point 202, in response todetermining that either a zone entry event or a zone exit event has beendetected responsive to a user either entering a zone or exiting a zoneof a venue, the process 200 begins measuring time to zone entry and/ortime to zone exit by other users, respectively, at block 212. Atdecision point 214, the process 200 makes a determination as to whetherat least one other user enters the same zone or exits the same zonewithin one of a configured zone entry time threshold or a configuredzone exit time threshold, as appropriate according to the respectivedetected zone entry event or zone exit event. The configured zone entrytime threshold defines a minimum time after a first user enters a zoneof the venue within which a second user must enter the zone to infer therelationship between the first user and the second user. The configuredzone exit time threshold defines a minimum time after a first user exitsa zone of the venue within which a second user must exit the zone toinfer the relationship between the first user and the second user. Inresponse to determining that no other user enters the same zone withinthe configured zone entry time threshold or that no other user exits thesame zone within the configured zone exit time threshold, the process200 determines that no group is available to be inferred from therespective zone entry event or zone exit event, and the process 200returns to decision point 204 and iterates as described above.Alternatively, in response to determining at decision point 214 that atleast one other user enters the same zone within the configured zoneentry time threshold or that at least one other user exits the same zonewithin the configured zone exit time threshold, the process 200 infers arelationship between the respective mobile device users at block 216. Assuch, the process 200 infers the relationship between the usersresponsive one of the users entering a zone of the venue and other usersentering the zone of the venue within the defined minimum time thatsatisfies the configured zone entry time threshold. The process 200 alsoinfers the relationship between the users responsive one of the usersexiting a zone of the venue and other users exiting the zone of thevenue within the defined minimum time that satisfies the configured zoneexit time threshold. The process 200 returns to decision point 202 anditerates as described above. The process 200 may alternatively return todecision point 204 as appropriate for a given implementation.

Returning to the description of decision point 204, in response todetermining that a zone movement distance event has been detectedresponsive to multiple users beginning to move together within aconfigured distance, the process 200 begins measuring time that theusers move together at block 218. At decision point 220, the process 200makes a determination as to whether the users move together within theconfigured distance for a configured movement distance-time threshold.The configured movement distance-time threshold defines a minimumdistance within which a first user and a second user must remain for aminimum time to infer the relationship between the first user and thesecond user. In response to determining that the users do not movetogether within the configured distance for the configured movementdistance-time threshold, the process 200 determines that no group isavailable to be inferred from the zone event and returns to decisionpoint 206 and iterates as described above. Alternatively, in response todetermining at decision point 220 that at least two users move togetherwithin the configured distance for the configured movement distance-timethreshold, the process 200 infers a relationship between the respectivemobile device users at block 216. As such, the process 200 infers therelationship between users responsive the users moving among and withinthe venue while remaining within a minimum distance of each other forthe defined minimum time that satisfies the configured movementdistance-time threshold. The process 200 returns to decision point 202and iterates as described above. The process 200 may alternativelyreturn to decision point 206 as appropriate for a given implementation.

Returning to the description of decision point 206, in response todetermining that a similar movement event has been detected responsiveto users making a similar movement within a venue (perhaps irrespectiveof a particular distance between the users and/or the timing of zoneentries), the process 200 begins measuring the number of times that theusers move together at block 222. At decision point 224, the process 200makes a determination as to whether the users move together for aconfigured similar movement count threshold. The configured similarmovement count threshold defines a minimum number of similar movementswithin the venue that a first user and a second user must make to inferthe relationship between the first user and the second user. In responseto determining that the users do not move together for the configuredsimilar movement count threshold, the process 200 determines that nogroup is available to be inferred from the zone event and returns todecision point 208 and iterates as described above. Alternatively, inresponse to determining at decision point 224 that at least two usersmove together for the configured similar movement count threshold, theprocess 200 infers a relationship between the respective mobile deviceusers at block 216. As such, the process 200 infers the relationshipbetween at least two of the users responsive the users moving togetherwithin the venue for the defined minimum number of similar movementsthat satisfies the configured similar movement count threshold. Theprocess 200 returns to decision point 202 and iterates as describedabove. The process 200 may alternatively return to decision point 208 asappropriate for a given implementation.

Returning to the description of decision point 208, in response todetermining that a shared dwell event has been detected responsive tomultiple users becoming stationary (e.g., standing) together within avenue, the process 200 begins measuring time that the users remain(e.g., dwell—stand, sit, etc.) together at block 226. At decision point228, the process 200 makes a determination as to whether the usersremain together for a configured shared dwell time threshold. Theconfigured shared dwell time threshold defines a minimum amount of timethat a first user and a second user must remain stationary and togetherwithin the venue to infer the relationship between the first user andthe second user. In response to determining that the users do not remainstationary and together for the configured shared dwell time threshold,the process 200 determines that no group is available to be inferredfrom the zone event and returns to decision point 210 and iterates asdescribed above. Alternatively, in response to determining at decisionpoint 228 that at least two users remain stationary and together for theconfigured shared dwell time threshold, the process 200 infers arelationship between the respective mobile device users at block 216. Assuch, the process 200 infers the relationship between the usersresponsive the users remaining stationary and together within the venuefor the defined minimum amount of time that satisfies the configuredshared dwell time threshold. The process 200 returns to decision point202 and iterates as described above. The process 200 may alternativelyreturn to decision point 210 as appropriate for a given implementation.

Returning to the description of decision point 210, in response todetermining that a common zones at common times event has been detectedresponsive to users being repeatedly detected within the same zones of avenue (e.g., multiple zone overlaps, again, perhaps irrespective of aparticular distance between the users and/or the timing of zoneentries), the process 200 begins measuring a number of common zones atcommon times events for the users at block 230. At decision point 232,the process 200 makes a determination as to whether the users haverepeatedly shared common zones at common times for a configured commonzones at common times threshold. The configured common zones at commontimes threshold defines a minimum number of zones of the venue that afirst user and a second user must be in together to infer therelationship between the first user and the second user. For example,the configured common zones at common times threshold may specify thatif users share the same venue zones for a certain percentage of time(e.g., fifty percent (50%), etc.), then a relationship may be inferredbetween the users. In response to determining that the users have notrepeatedly shared common zones at common times for the configured commonzones at common times threshold, the process 200 determines that nogroup is available to be inferred from the zone event and returns todecision point 202 and iterates as described above. Alternatively, inresponse to determining at decision point 232 that at least two usershave repeatedly shared common zones at common times for the configuredcommon zones at common times threshold, the process 200 infers arelationship between the respective mobile device users at block 216. Assuch, the process 200 infers the relationship between the usersresponsive to the users being together within a minimum number of zonesof the venue that satisfies the configured common zones at common timesthreshold. The process 200 returns to decision point 202 and iterates asdescribed above.

As such, the process 200 provides example processing for severaldifferent venue zone events that may be used to infer relationshipsbetween users of mobile devices, and to thereby perform group inferencebased upon venue zone events. The venue zone events may be definedgranularly as appropriate for a particular implementation.

As described above in association with FIG. 1 through FIG. 5, theexample systems and processes provide group inference based upon venuezone events. Many other variations and additional activities associatedwith group inference based upon venue zone events are possible and allare considered within the scope of the present subject matter.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a,” “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the art basedupon the teachings herein without departing from the scope and spirit ofthe invention. The subject matter was described to explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

1. A computer-implemented method, comprising: by a processor;establishing multiple configured zones within a venue, with eachconfigured zone differentiated within the venue using at least one of aplurality of short-distance wireless device location detection sensorspositioned within the venue to detect movement of mobile devices acrossboundaries of and within the respective configured zone; tracking,within the venue using the plurality of short-distance wireless devicelocation detection sensors, zone events that represent (i) differencesof relative movements of multiple mobile devices, (ii) coincidentmovements of the multiple mobile devices, and (iii) dwelling times ofthe multiple mobile devices within the venue as users of the respectivemobile devices (i) move across the boundaries of, (ii) move within, and(iii) dwell within the multiple configured zones of the venue; andinferring a relationship between at least two of the users responsive toa configured zone event threshold being satisfied by the tracked zoneevents that represent (i) the differences of the relative movements ofthe multiple mobile devices, (ii) the coincident movements of themultiple mobile devices, and (iii) the dwelling times of the mobiledevices of the at least two users.
 2. The computer-implemented method ofclaim 1, where: the configured zone event threshold comprises one of: aconfigured zone entry time threshold that defines a minimum time after afirst user enters a configured zone of the venue within which a seconduser must enter the configured zone to infer the relationship betweenthe first user and the second user; and a configured zone exit timethreshold that defines a minimum time after a first user exits theconfigured zone of the venue within which a second user must exit theconfigured zone to infer the relationship between the first user and thesecond user; and inferring the relationship between the at least two ofthe users responsive to the configured zone event threshold beingsatisfied by the tracked zone events that represent the relativemovements and dwelling times of the mobile devices of the at least twousers comprises: where the configured zone event threshold comprises theconfigured zone entry time threshold, inferring the relationship betweenthe at least two of the users responsive to one of the at least twousers entering the configured zone of the venue and another of the atleast two users entering the configured zone of the venue within thedefined minimum time that satisfies the configured zone entry timethreshold; and where the configured zone event threshold comprises theconfigured zone exit time threshold, inferring the relationship betweenthe at least two of the users responsive to one of the at least twousers exiting the configured zone of the venue and another of the atleast two users exiting the configured zone of the venue within thedefined minimum time that satisfies the configured zone exit timethreshold.
 3. The computer-implemented method of claim 1, where: theconfigured zone event threshold comprises a configured movementdistance-time threshold that defines a minimum distance from each otherthat a first user and a second user must remain for a minimum time while(i) moving across the boundaries of and (ii) moving within the multipleconfigured zones of the venue to infer the relationship between thefirst user and the second user; and inferring the relationship betweenthe at least two of the users responsive to the configured zone eventthreshold being satisfied by the tracked zone events that represent therelative movements and dwelling times of the mobile devices of the atleast two users comprises: inferring the relationship between the atleast two of the users responsive to the at least two users remainingwithin the defined minimum distance from each other for the minimum timewhile (i) moving across the boundaries of and (ii) moving within themultiple configured zones of the venue that satisfies the configuredmovement distance-time threshold.
 4. The computer-implemented method ofclaim 1, where: the configured zone event threshold comprises aconfigured similar movement count threshold that defines a minimumnumber of the coincident movements (i) across the boundaries of and (ii)within the multiple configured zones of the venue that a first user anda second user must make to infer the relationship between the first userand the second user; and inferring the relationship between the at leasttwo of the users responsive to the configured zone event threshold beingsatisfied by the tracked zone events that represent the relativemovements and dwelling times of the mobile devices of the at least twousers comprises: inferring the relationship between the at least two ofthe users responsive to the at least two users moving together for thedefined minimum number of the coincident movements (i) across theboundaries of and (ii) within the multiple configured zones of the venuethat satisfies the configured similar movement count threshold.
 5. Thecomputer-implemented method of claim 1, where: the configured zone eventthreshold comprises a configured shared dwell time threshold thatdefines a minimum amount of time that a first user and a second usermust remain together within the multiple configured zones of the venueto infer the relationship between the first user and the second user;and inferring the relationship between the at least two of the usersresponsive to the configured zone event threshold being satisfied by thetracked zone events that represent the relative movements and dwellingtimes of the mobile devices of the at least two users comprises:inferring the relationship between the at least two of the usersresponsive to the at least two users remaining together for the definedminimum amount of time within the multiple configured zones of the venuethat satisfies the configured shared dwell time threshold.
 6. Thecomputer-implemented method of claim 1, where: the configured zone eventthreshold comprises a configured common zones at common times thresholdthat defines a minimum number of the multiple configured zones of thevenue that a first user and a second user must be in together to inferthe relationship between the first user and the second user; andinferring the relationship between the at least two of the usersresponsive to the configured zone event threshold being satisfied by thetracked zone events that represent the relative movements and dwellingtimes of the mobile devices of the at least two users comprises:inferring the relationship between the at least two of the usersresponsive to the at least two users being together in the definedminimum number of the multiple configured zones of the venue thatsatisfies the configured common zones at common times threshold.
 7. Thecomputer-implemented method of claim 1, where the at least one of thetracking and the inferring are provided as part of a service in a cloudenvironment.
 8. A system, comprising: a memory; and a processorprogrammed to: establish multiple configured zones of a venue, with eachconfigured zone differentiated within the venue using at least one of aplurality of short-distance wireless device location detection sensorspositioned within the venue to detect movement of mobile devices acrossboundaries of and within the respective configured zone; track, withinthe venue using the plurality of short-distance wireless device locationdetection sensors, zone events that represent (i) differences ofrelative movements of multiple mobile devices, (ii) coincident movementsof the multiple mobile devices, and (iii) dwelling times of the multiplemobile devices within the venue as users of the respective mobiledevices (i) move across the boundaries of, (ii) move within, and (iii)dwell within the multiple configured zones of the venue; and inferwithin the memory a relationship between at least two of the usersresponsive to a configured zone event threshold being satisfied by thetracked zone events that represent (i) the differences of the relativemovements of the multiple mobile devices, (ii) the coincident movementsof the multiple mobile devices, and (iii) the dwelling times of themobile devices of the at least two users.
 9. The system of claim 8,where: the configured zone event threshold comprises one of: aconfigured zone entry time threshold that defines a minimum time after afirst user enters a configured zone of the venue within which a seconduser must enter the configured zone to infer the relationship betweenthe first user and the second user; and a configured zone exit timethreshold that defines a minimum time after a first user exits theconfigured zone of the venue within which a second user must exit theconfigured zone to infer the relationship between the first user and thesecond user; and in being programmed to infer within the memory therelationship between the at least two of the users responsive to theconfigured zone event threshold being satisfied by the tracked zoneevents that represent the relative movements and dwelling times of themobile devices of the at least two users, the processor is programmedto: where the configured zone event threshold comprises the configuredzone entry time threshold, infer within the memory the relationshipbetween the at least two of the users responsive to one of the at leasttwo users entering the configured zone of the venue and another of theat least two users entering the configured zone of the venue within thedefined minimum time that satisfies the configured zone entry timethreshold; and where the configured zone event threshold comprises theconfigured zone exit time threshold, infer within the memory therelationship between the at least two of the users responsive to one ofthe at least two users exiting the configured zone of the venue andanother of the at least two users exiting the configured zone of thevenue within the defined minimum time that satisfies the configured zoneexit time threshold.
 10. The system of claim 8, where: the configuredzone event threshold comprises a configured movement distance-timethreshold that defines a minimum distance from each other that a firstuser and a second user must remain for a minimum time while (i) movingacross the boundaries of and (ii) moving within the multiple configuredzones of the venue to infer the relationship between the first user andthe second user; and in being programmed to infer within the memory therelationship between the at least two of the users responsive to theconfigured zone event threshold being satisfied by the tracked zoneevents that represent the relative movements and dwelling times of themobile devices of the at least two users, the processor is programmedto: infer within the memory the relationship between the at least two ofthe users responsive to the at least two users remaining within thedefined minimum distance from each other for the minimum time while (i)moving across the boundaries of and (ii) moving within the multipleconfigured zones of the venue that satisfies the configured movementdistance-time threshold.
 11. The system of claim 8, where: theconfigured zone event threshold comprises a configured similar movementcount threshold that defines a minimum number of the coincidentmovements (i) across the boundaries of and (ii) within the multipleconfigured zones of the venue that a first user and a second user mustmake to infer the relationship between the first user and the seconduser; and in being programmed to infer within the memory therelationship between the at least two of the users responsive to theconfigured zone event threshold being satisfied by the tracked zoneevents that represent the relative movements and dwelling times of themobile devices of the at least two users, the processor is programmedto: infer within the memory the relationship between the at least two ofthe users responsive to the at least two users moving together for thedefined minimum number of the coincident movements (i) across theboundaries of and (ii) within the multiple configured zones of the venuethat satisfies the configured similar movement count threshold.
 12. Thesystem of claim 8, where: the configured zone event threshold comprisesa configured shared dwell time threshold that defines a minimum amountof time that a first user and a second user must remain together withinthe multiple configured zones of the venue to infer the relationshipbetween the first user and the second user; and in being programmed toinfer within the memory the relationship between the at least two of theusers responsive to the configured zone event threshold being satisfiedby the tracked zone events that represent the relative movements anddwelling times of the mobile devices of the at least two users, theprocessor is programmed to: infer within the memory the relationshipbetween the at least two of the users responsive to the at least twousers remaining together for the defined minimum amount of time withinthe multiple configured zones of the venue that satisfies the configuredshared dwell time threshold.
 13. The system of claim 8, where: theconfigured zone event threshold comprises a configured common zones atcommon times threshold that defines a minimum number of the multipleconfigured zones of the venue that a first user and a second user mustbe in together to infer the relationship between the first user and thesecond user; and in being programmed to infer within the memory therelationship between the at least two of the users responsive to theconfigured zone event threshold being satisfied by the tracked zoneevents that represent the relative movements and dwelling times of themobile devices of the at least two users, the processor is programmedto: infer within the memory the relationship between the at least two ofthe users responsive to the at least two users being together in thedefined minimum number of the multiple configured zones of the venuethat satisfies the configured common zones at common times threshold.14. A computer program product, comprising: a computer readable storagemedium having computer readable program code embodied therewith, wherethe computer readable storage medium is not a transitory signal per seand where the computer readable program code when executed on a computercauses the computer to: establish multiple configured zones of a venue,with each configured zone differentiated within the venue using at leastone of a plurality of short-distance wireless device location detectionsensors positioned within the venue to detect movement of mobile devicesacross boundaries of and within the respective configured zone; track,within the venue using the plurality of short-distance wireless devicelocation detection sensors, zone events that represent (i) differencesof relative movements of multiple mobile devices, (ii) coincidentmovements of the multiple mobile devices, and (iii) dwelling times ofthe multiple mobile devices within the venue as users of the respectivemobile devices (i) move across the boundaries of, (ii) move within, and(iii) dwell within the multiple configured zones of the venue; and infera relationship between at least two of the users responsive to aconfigured zone event threshold being satisfied by the tracked zoneevents that represent (i) the differences of the relative movements ofthe multiple mobile devices, (ii) the coincident movements of themultiple mobile devices, and (iii) the dwelling times of the mobiledevices of the at least two users.
 15. The computer program product ofclaim 14, where: the configured zone event threshold comprises one of: aconfigured zone entry time threshold that defines a minimum time after afirst user enters a configured zone of the venue within which a seconduser must enter the configured zone to infer the relationship betweenthe first user and the second user; and a configured zone exit timethreshold that defines a minimum time after a first user exits theconfigured zone of the venue within which a second user must exit theconfigured zone to infer the relationship between the first user and thesecond user; and in causing the computer to infer the relationshipbetween the at least two of the users responsive to the configured zoneevent threshold being satisfied by the tracked zone events thatrepresent the relative movements and dwelling times of the mobiledevices of the at least two users, the computer readable program codewhen executed on the computer causes the computer to: where theconfigured zone event threshold comprises the configured zone entry timethreshold, infer the relationship between the at least two of the usersresponsive to one of the at least two users entering the configured zoneof the venue and another of the at least two users entering theconfigured zone of the venue within the defined minimum time thatsatisfies the configured zone entry time threshold; and where theconfigured zone event threshold comprises the configured zone exit timethreshold, infer the relationship between the at least two of the usersresponsive to one of the at least two users exiting the configured zoneof the venue and another of the at least two users exiting theconfigured zone of the venue within the defined minimum time thatsatisfies the configured zone exit time threshold.
 16. The computerprogram product of claim 14, where: the configured zone event thresholdcomprises a configured movement distance-time threshold that defines aminimum distance from each other that a first user and a second usermust remain for a minimum time while (i) moving across the boundaries ofand (ii) moving within the multiple configured zones of the venue toinfer the relationship between the first user and the second user; andin causing the computer to infer the relationship between the at leasttwo of the users responsive to the configured zone event threshold beingsatisfied by the tracked zone events that represent the relativemovements and dwelling times of the mobile devices of the at least twousers, the computer readable program code when executed on the computercauses the computer to: infer the relationship between the at least twoof the users responsive to the at least two users remaining within thedefined minimum distance from each other for the minimum time while (i)moving across the boundaries of and (ii) moving within the multipleconfigured zones of the venue that satisfies the configured movementdistance-time threshold.
 17. The computer program product of claim 14,where: the configured zone event threshold comprises a configuredsimilar movement count threshold that defines a minimum number of thecoincident movements (i) across the boundaries of and (ii) within themultiple configured zones of the venue that a first user and a seconduser must make to infer the relationship between the first user and thesecond user; and in causing the computer to infer the relationshipbetween the at least two of the users responsive to the configured zoneevent threshold being satisfied by the tracked zone events thatrepresent the relative movements and dwelling times of the mobiledevices of the at least two users, the computer readable program codewhen executed on the computer causes the computer to: infer therelationship between the at least two of the users responsive to the atleast two users moving together for the defined minimum number ofcoincident movements (i) across the boundaries of and (ii) within themultiple configured zones of the venue that satisfies the configuredsimilar movement count threshold.
 18. The computer program product ofclaim 14, where: the configured zone event threshold comprises aconfigured shared dwell time threshold that defines a minimum amount oftime that a first user and a second user must remain together within themultiple configured zones of the venue to infer the relationship betweenthe first user and the second user; and in causing the computer to inferthe relationship between the at least two of the users responsive to theconfigured zone event threshold being satisfied by the tracked zoneevents that represent the relative movements and dwelling times of themobile devices of the at least two users, the computer readable programcode when executed on the computer causes the computer to: inferring therelationship between the at least two of the users responsive to the atleast two users remaining together for the defined minimum amount oftime within the multiple configured zones of the venue that satisfiesthe configured shared dwell time threshold.
 19. The computer programproduct of claim 14, where: the configured zone event thresholdcomprises a configured common zones at common times threshold thatdefines a minimum number of the multiple configured zones of the venuethat a first user and a second user must be in together to infer therelationship between the first user and the second user; and in causingthe computer to infer the relationship between the at least two of theusers responsive to the configured zone event threshold being satisfiedby the tracked zone events that represent the relative movements anddwelling times of the mobile devices of the at least two users, thecomputer readable program code when executed on the computer causes thecomputer to: infer the relationship between the at least two of theusers responsive to the at least two users being together in the definedminimum number of the multiple configured zones of the venue thatsatisfies the configured common zones at common times threshold.
 20. Thecomputer program product of claim 14, where the at least one of thetracking and the inferring are provided as part of a service in a cloudenvironment.